This study examines the effectiveness of game-based learning in enhancing hazard identification skills. The research employed a mixed-methods approach, combining quantitative analysis of participants’ hazard identification performance and eye-tracking data with qualitative insights from participant feedback. In a simulated study, participants were asked to identify hazards following the game-based training intervention. The Hazard Identification Index (HII) scores increased significantly (p < 0.0001) in the post-training trials, indicating enhanced hazard recognition abilities. The analysis of eye-tracking data revealed changes in participants’ attention allocation patterns in the post-training trials. Furthermore, the study highlights the importance of minimizing task interruptions during hazard identification activities, as interruptions negatively impacted participants’ performance. The findings of this study have significant implications for training programs focused on workplace safety. Integrating game-based learning in safety training programs can help employers enhance hazard identification skills among their employees, ultimately contributing to safer work environments and reducing incidents of accidents and injuries.

Motivated by the rapid technological advancements achieved in the last five years and the pervasiveness of Artificial Intelligence (AI), this paper investigates the evolving role of HCI and revisits the seven grand challenges outlined in 2019: human-technology symbiosis, human-environment interactions, ethics, privacy and security, well-being, health and eudaimonia, accessibility and universal access, learning and creativity, and social organization and democracy. Through literature analysis, the paper reevaluates the status of each challenge and highlights emerging requirements. Key findings reveal the widespread impact of AI across all domains and emphasize the need for improved AI transparency, alignment with human values, and the development of explainable, personalized, and privacy-preserving technologies to enhance user trust and control. The analysis also highlights the interconnected nature of these challenges and firmly asserts the role of technology in actively supporting human activities and collaborating harmoniously with humans to help them live meaningfully and fulfill aspirations.

Smart service systems leverage ubiquitous computing capabilities, connectivity, data storage, analytics, and a variety of types of sensors to provide value co-creation for intended users and the or...

Application icons are a pivotal part of graphical user interface of mobile devices. Despite a trend away from complexity to simplicity in user interface design, there is lack of evidence supporting the superiority of icon simplicity from a psychophysiological perspective. This study investigates the effects of icon complexity and simplicity on user cognition using an event-related potentials (ERPs) technique. Eighteen participants completed an icon cognition and evaluation experiment in an electrophysiological laboratory. Their subjective evaluations, behavioral data, and ERP data were recorded and analyzed. The results of subjective evaluation showed that the simplest icons were regarded as more useful in helping subjects extract icon information than more complex ones. For the ERP measures, P1 amplitudes induced by complex icons were larger than those elicited by simple icons. In the parietal area, P2 amplitudes and latency were larger and later for complex icons than for simple ones. Simple icons are subjectively more helpful than complex ones, partially because they demand fewer attention resources in early stimulus-driven perceptual detection of icon features (P1 during 120–190 ms) and induce more positive emotional arousal (P2 during 190–200 ms). Simple icon designs minimize cognitive demands and are deemed more helpful than complex ones. Our study highlights that the ERP technique represents a tool to explore how users process icon and interface design.

The rapid development of robot technology has introduced a substantial impact on manufacturing. Numerous studies have been carried out to apply collaborative robots (cobots) to address manufacturing productivity and ergonomics issues, which has brought extensive opportunities. In this context, a systematic literature search in the Web of Science, Scopus, and Google Scholar databases was carried out by electronic and manual search. Thus, 59 relevant contributions out of 4488 studies were analyzed by using preferred reporting items for systematic reviews and meta-analysis (PRISMA). To provide an overview of the different results, studies are summarized according to the following criteria: country, author, year, study design, robot category, results, and future opportunities. The effects of cobots on safety, system design, workplace design, task scheduling, productivity, and ergonomics are discussed to provide a better understanding of the application of cobots in manufacturing. To incentive future research, this paper reviews the development of cobots in manufacturing and discusses future opportunities and directions from cobots and manufacturing system perspectives. This paper provides novel and valuable insights into cobots application and illustrates potential developments of future human-cobot interaction.

The present study aimed to investigate how facial features, including facial ratio, eye shape, and mouth presence, influence users’ perceptions of social robots in terms of anthropomorphism, trustworthiness, and overall impressions. Using electroencephalogram (EEG) and eye-tracking technologies, we conducted a 2 (face ratio) × 2 (eye shape) × 2 (with or without mouth) full factorial experiment designed within-subject. EEG signals and pupil diameters were recorded while participants viewed images of robots with different facial design features. The results showed that the shape of robot’s eyes significantly influenced users’ perceptions, with round eyes being associated with higher ratings of anthropomorphism, trustworthiness, and overall positivity. Robots with lower facial width-to-height ratios (fWHR) induced smaller average pupil diameters in users than those with high fWHR. Additionally, robots with lower fWHR were perceived as more anthropomorphic, trustworthy and users produced higher theta rhythm when the eye shape was round but did not when it was rectangular. The presence of a mouth led to higher ratings of anthropomorphism rather than trustworthiness and other measures. Overall, the findings highlight the importance of facial features in shaping users’ perceptions of social robots and provide practical implications for designing social robots with anthropomorphic facial features.

With the development of automated driving systems and V2I (vehicle-to-infrastructure) communications, soft-safety driver alerts can be implemented to supplement imminent driver alerts. This type of alert improves drivers’ situational awareness of emerging risks over a more extended period with more detailed incident information and longer response time. However, compared to the large number of studies focusing on imminent risks, there are insufficient studies on the evaluation and effectiveness of soft-safety alerts. This study proposed an innovative metric to assess the comfort and safety of soft-safety driver alerts by constructing an ideal speed profile and calculating the deviation between the actual and ideal profile. We select the highway end-of-queue event as the experiment scenario, which is a leading cause of fatal highway crashes. Human subjects’ experiments are conducted in the driving simulator to validate the proposed metrics. The results have proved that the proposed metrics have good potential to assess driving comfort objectively. We also found that soft-safety alerts tend to improve driving comfort. However, there is insufficient evidence to conclude statistically about the prototype soft-safety alerts implemented in the experiments.

Users’ affective preference for voices has become a topic of great interest with the prevalence of humanoid robots. Nevertheless, the affective preference formation for humanoid voices remains unknown, and its evaluation lacks objective methods. Consequently, we conducted an EEG experiment to unravel the underlying neural dynamics and evaluate users’ affective preference for humanoid robot voices. Significantly larger P2, P3, and LPP amplitudes, enhanced theta, and decreased alpha oscillations were observed when users affectively preferred humanoid robot voices. The results suggest that the neural dynamics underlying users’ affective preference for humanoid robot voices might primarily consist of early detection of affective information in voices, further processing of affective information, and later evaluative categorization of affective preference. Moreover, the neural indicators could distinguish users’ affective preferences for humanoid robot voices. The study contributes to understanding the auditory affective preference formation for humanoid robot voices and providing a neurological evaluation method.

Even though humanoid robots are being applied to diverse areas, the formation of users’ preference for the appearance of humanoid robots remains unknown. The present study investigated users’ neural dynamics underlying preference formation to evaluate users’ preference for the appearance of humanoid robots. EEG signals were recorded in a preference categorisation task, and neural dynamics were analysed via event-related potentials and time–frequency analysis. The results showed that in the early stage, the preferred humanoid robot appearances elicited enhanced parieto-occipital N1, frontal P2, and early central and parieto-occipital theta rhythm power than the non-preferred appearances. In the later stage, the preferred humanoid robot appearances elicited enhanced scalp-distributed LPP and later central and parieto-occipital theta power than the non-preferred appearances. The results suggested that the formation of users’ preference for the appearance of humanoid robots has a distinctive dual-stage of neural dynamics. The study provides designers with an objective method in evaluating users’ preference for the appearance of humanoid robots.

The effective use of computational modeling and simulation tools early in the design process is arguably becoming a gold standard for modern product development. Compared to many mechanistic computational design approaches, modeling and simulating humans, due to their inherent complexities of physiological and cognitive attributes, provides one of the most challenging undertakings. With the rapidly expanding use of computer, sensor, and visualization technologies, digital human modeling (DHM) emerged as a computerized design support methodology that enables modeling and simulation of humans within a computer-aided design (CAD) or virtual environment (VE). Implementing DHM with physical or digital mockups brings the advantages of running various “what-if” design scenarios early in design; thus, enhancing concept generation efforts by filtering out infeasible ideas and exploring better design alternatives. A modern product development process with DHM can also help to reduce the overall cost and time required in the long run. Although several DHM software packages are available and many companies have been designing with DHM, the domain has not reached maturity in resolving theoretical research questions and fostering simulation-based ergonomics practice. Besides, the growing body of literature, software platforms, and technology integration makes it challenging for newcomers and specialists from disciplines other than human factors engineering (HFE) to recognize the power of DHM tools. This paper aims to provide a comprehensive review of the DHM domain and summarize the evolution, current status, and future trends of the DHM design support tools. We hope this review will provide a guideline for designers and serve as a roadmap for current and future researchers interested in DHM-related research to find out new venues and opportunities for further international collaborations.

We investigated the impact of color salience and location of a website link on users’ performance, affective experiences and approach-avoidance tendencies with 10 mock mobile Web directories. Task completion times were recorded by a computer program, and users’ affective experiences and approach-avoidance responses were reported in questionnaires. Results implied that visual attention in the display area on a mobile Web directory is directed by a combination of bottom-up and top-down processes, which is different from the primarily top-down process implicated in a similar study of PC Web directories. A salient color of the website link helped attract users’ attention and increase users’ sense of control over the process. Also, users are likely to search webpages from top left to bottom right. Our findings suggest that a target website link placed in the top left corner or displayed in a distinct color in the center area not only attracts users’ attention but also results in a more highly rated affective experience. Color of the target website link can be changed to increase users’ sense of control of a Web directory and approach behaviors.

UX (User experience) can influence important user behaviors, including user preference, purchasing decisions, and customer loyalty. The ability to assess UX during the product trial has practical significance for design and improvement of products. In this article, two smartphones with different UX were selected through a focus group. In the EEG (electroencephalography) experiment, we explored the brain signal of users when using two smartphones to complete three tasks. The brain signal of each participant was recorded through Curry Neuroimaging Suite software (Version 7.0, Compumedics Limited, Abbotsford, Australia) when they were using the smartphones. Then results from behavioral, subjective and neural responses were analyzed. The behavioral results showed that participants completed the three tasks faster by using a smartphone with a higher score of UX. The subjective results showed a significant difference between the two smartphones. The patterns of cortical activity were obtained in the five principal frequency bands, Delta (1–4 Hz), Theta (4–8 Hz), Alpha (8–13 Hz), Beta (13–30 Hz) and Gamma (30–45 Hz). The results indicated that a smartphone with higher scores of UX could evoke stronger relative power of Alpha (fronto-central, parietal and partieto-occipital regions), Delta (frontal region) and Gamma rhythms (C3 site), but weaker relative power of Beta (left central region) and Theta rhythms (frontal and parieto-occipital regions). Also, the correlation analysis showed that there was no significant relationship between EEG and behavioral results. User’s subjective experience had a significant positive correlation with the relative power of Gamma band, but a negative correlation with Beta and Theta bands (approximately significant with p = .078 and p = .071). There were also significant correlations between EEG results and sub-items of UX. Our findings suggest that the difference in EEG may be taken as an evaluating indicator of user perception when using products without interruption.

Affective computing focuses on technologies and theories that advance understanding of human affect, considering emotion and cognition in the design of related technologies to fulfill human needs, which gains substantial attention of researchers all over the world. To provide an insight into affective computing researches, this paper utilizes the method of bibliometric analysis to obtain information with respect to when and where the researches were performed by whom and how the mainstream contents evolved over the years. BibExcel and CiteSpace were employed to conduct the performance analysis and co-citation network analysis, including the analysis of the performance of countries, journals, institutes, authors and research hotspots. A total number of 1,625 documents published from 1999 ~ 2018 were screened to conduct quantitative analysis, which were retrieved in the Web of Science database with defined search terms. This paper can enable researchers to gain wider and deeper insight into affective computing researches in the last decades through bibliometric analysis, thereby facilitating relevant researchers having a general understanding of aggregate performance in the affective computing field and finding research directions in the future.

An Object-Oriented User Interface Customization (OOUIC) framework has been previously proposed as a systematic approach toward reducing the complexity and improving usability and user performance. The OOUIC suggests combining adaptive and adaptable User Interfaces (UIs). Adaptive UIs reduce complexity while adaptable UIs enable customization for specific needs. The objective of this paper is to assess the combination of adaptive and adaptable UIs for improving usability and user performance of complex UIs. Complex UIs are the original interfaces of a complex system. Adaptive UIs automatically tailor UIs to be relevant to a user role but fail to satisfy an individual’s unique needs. Adaptable UIs enable a user to adjust UIs to meet needs for achieving specific tasks but are hard to use. Combining these two techniques enables users to customize complex UIs more easily. This research can be applied directly to the design and redesign of Product Lifecycle Management (PLM) systems. These systems have been consistently enhanced for their lack of usability. In this study complex UIs, adaptive UIs, adaptable UIs, and combination UIs were assessed by measuring 96 participants’ perceived usability, task time, and eye tracking data. Significant results were found on usability score (F (3, 189) = 12.14, p < .001), time spent (F (3, 189) = 63.40, p < .001), and fixation count (F (3, 189) = 39.72, p < .001), indicating that adaptive, adaptable, and combination UIs had better usability and user performance than complex UIs. The usability of combination UIs and adaptable UIs was better than adaptive UIs. Combining adaptive and adaptable UIs can facilitate users to simplify complex UIs.

Web directories have attracted many advertisers with their special advantages in their large user base. Until recently, attention mechanism of advertisements (ad) on web directories is not well understood. To investigate how the ad location and color of web directories influence users’ attention, this study uses eye tracking to measure the participants’ search time, total fixation duration and the location of the first fixation. Results reveal that visual attention on the ad area of a web directory is user-driven and follows a top-down process. The location of users’ first-fixations is the center of the screen. Ad links that place in the center area and on the top-left corner would increase users’ notice. Ad links that change color in the center area have the advantages of attracting user attention. Our findings suggest that ad links should be placed in the center area or on the top-left corner to increase users’ notice. Ad links placed in the center area should be designed using salient color to catch users’ visual attention.

The design of humanoid robots’ emotional behaviors has attracted many scholars’ attention. However, users’ emotional responses to humanoid robots’ emotional behaviors which differ from robots’ traditional behaviors remain well understood. This study aims to investigate the effect of a humanoid robot’s emotional behaviors on users’ emotional responses using subjective reporting, pupillometry, and electroencephalography. Five categories of the humanoid robot’s emotional behaviors expressing joy, fear, neutral, sadness, or anger were designed, selected, and presented to users. Results show that users have a significant positive emotional response to the humanoid robot’s joy behavior and a significant negative emotional response to the humanoid robot’s sadness behavior, indicated by the metrics of reported valence and arousal, pupil diameter, frontal middle relative theta power, and frontal alpha asymmetry score. The results suggest that humanoid robot’s emotional behaviors can evocate users’ significant emotional response. The evocation might relate to the recognition of these emotional behaviors. In addition, the study provides a multimodal physiological method of evaluating users’ emotional responses to the humanoid robot’s emotional behaviors.

Published with license by Taylor & Francis Group, LLC. This article aims to investigate the Grand Challenges which arise in the current and emerging landscape of rapid technological evolution towards more intelligent interactive technologies, coupled with increased and widened societal needs, as well as individual and collective expectations that HCI, as a discipline, is called upon to address. A perspective oriented to humane and social values is adopted, formulating the challenges in terms of the impact of emerging intelligent interactive technologies on human life both at the individual and societal levels. Seven Grand Challenges are identified and presented in this article: Human-Technology Symbiosis; Human-Environment Interactions; Ethics, Privacy and Security; Well-being, Health and Eudaimonia; Accessibility and Universal Access; Learning and Creativity; and Social Organization and Democracy. Although not exhaustive, they summarize the views and research priorities of an international interdisciplinary group of experts, reflecting different scientific perspectives, methodological approaches and application domains. Each identified Grand Challenge is analyzed in terms of: concept and problem definition; main research issues involved and state of the art; and associated emerging requirements. BACKGROUND This article presents the results of the collective effort of a group of 32 experts involved in the community of the Human Computer Interaction International (HCII) Conference series. The group’s collaboration started in early 2018 with the collection of opinions from all group members, each asked to independently list and describe five HCI grand challenges. During a one-day meeting held on the 20th July 2018 in the context of the HCI International 2018 Conference in Las Vegas, USA, the identified topics were debated and challenges were formulated in terms of the impact of emerging intelligent interactive technologies on human life both at the individual and societal levels. Further analysis and consolidation led to a set of seven Grand Challenges presented herein. This activity was organized and supported by the HCII Conference series.

Integrated multimodal systems is one promising direction to improve human-vehicle interaction. In order to create intelligent human-vehicle interfaces and reduce visual load during secondary tasks, combining a haptic rotary device and a graphic display will provide one practical solution. However, in literature, the proper display position for the haptic rotary device is not fully investigated. In this paper, one experimental infotainment system is studied (including a haptic rotary control device and a graphic display) to evaluate the proper display position. Measurements used include task completion time, reaction to road events, lane/velocity keeping during secondary tasks, and user preference. Three display positions are considered: high mounted position, cluster position, and center stack position. The results show that, with increased on-road and off-road visual loads, the cluster display position can reduce lane position deviation significantly compared to high mounted and center stack positions. In addition, the high mounted and cluster display positions are better toward two different road events, including strong wind gust and extreme deceleration of the lead car.